Use sparse version susie (code not included)

library(Matrix)
library(ggplot2)
library(microbenchmark)
library(profvis)

Data

We use a specific gene set generated from susie-gsea-0806 and investigate the speed of sparse version SuSiE on this GSEA data set.

ygsea.sun = readRDS('sun_ygsea.rds')
Xgsea.sun = readRDS('sun_Xgsea.rds')
Xgsea.sun.sparse = Xgsea.sun
Xgsea.sun.dense = as.matrix(Xgsea.sun)

Use profvis to evaluate computational time line by line

profvis({
  susie.dense.fit = susie(Xgsea.sun.dense,ygsea.sun)
})
profvis({
  susie.sparse.fit = susie(Xgsea.sun.sparse,ygsea.sun)
})

Microbenchmark visualization

sparse.dense.test = microbenchmark(
  susie.sparse = susie(Xgsea.sun.sparse,ygsea.sun),
  susie.dense = susie(Xgsea.sun.dense,ygsea.sun),
  times=5
)
autoplot(sparse.dense.test)
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.